The University of Maryland (UMD) invites applications for a postdoctoral associate position in the Department of Environmental Science and Technology (ENST). Sponsored by Hughes Center for Agroecology- College of Agriculture and Natural Resources, this position will include a competitive salary and benefits. The position is available beginning as soon as someone appropriate is found.
Job Summary: The Postdoctoral Associate will join a team composed of diverse expertise who have secured funding to perform Climate Vulnerability of Maryland Agriculture. It is expected that the Postdoc to work closely with the PI and other team members to advance the research related to Climate Vulnerability of Maryland Agriculture. He/she will compile and synthesize data provided by other team members on the impact of climate on overall production system (i.e., impact on plant diseases, insects, crop yield, animal production, water resources, etc.). He/she is expected to develop multi-regression models using machine-learning technologies (e.g., Random Forest) that can link such climate impacts on agroecosystem to the climate parameters such as Temperature and Precipitation both in the past and future. Finally, it is expected that the Postdoc with the support of PI and other team members will move the outcome of the project to publication and dissemination stage.
Duties and Responsibilities: The Postdoctoral Associate will report to Professor Adel Shirmohammadi (PI), while collaborating with other team members. The Postdoctoral Associate will also contribute to developing additional proposal efforts, thereby strengthening UMD’s ability to attract external funding. The Postdoctoral Associate’s principal research responsibilities will be:
1- In Collaboration with PI, the other team members, and their graduate students, compile and synthesize trends on the impact for climate factors such as temperature, precipitation, humidity, etc. on overall crop and animal production for last 20-30 years. (25%).
2- Develop Multi-regression models using Machine-Learning (e.g., Random Forest) technology to link climate impacts on multiple aspects of crop and animal production for last 20-30 years. Using such regression models forecast the future climate impacts on multiple components of agroecosystem such as plant disease, insect damage, crop and animal yield, water resources, economic impacts, etc. One of the team members from the Atmospheric Science Department at UMD will provide the climate data. Other team members will provide data for each component of the Agroecosystem as appropriate with their expertise. (50%).
3- Help PI to prepare, write, and submit quarterly reports to the funding agency and assemble manuscripts to peer reviewed journals and present at research conferences in collaboration with the PI and other co-PIs/Team members (20%).
4- Help the team in communication with the stakeholders and the climate coordinator at the Hughes Center for Agroecology. (5%)
Minimum Qualifications: Background in one of the following disciplines is highly desirable: biological and agricultural engineering, environmental engineering/science, and data sciences/systems modeling. Preference will be given to candidates who possess strong computational skills, working experience in Machine-Learning methods, and expertise in data analysis and statistical modeling.
Contact: Adel Shirmohammadi (ashirmo@umd.edu)
